code: def postprocess(
      data_out,
      org_im,
      org_im_shape,
      org_im_path,
      output_dir,
      visualization,
  ):
      """
      Postprocess output of network. one image at a time.
  
      Args:
          data_out (numpy.ndarray): output of network.
          org_im (numpy.ndarray): original image.
          org_im_shape (list): shape pf original image.
          org_im_path (list): path of riginal image.
          output_dir (str): output directory to store image.
          visualization (bool): whether to save image or not.
  
      Returns:
          result (dict): The data of processed image.
      """
      result = dict()
      for sr in data_out:
          sr = np.squeeze(sr, 0)
          sr = np.clip(sr * 255, 0, 255)
          sr = sr.astype(np.uint8)
          sr = cv2.cvtColor(sr, cv2.COLOR_RGB2BGR)
  
          if visualization:
              check_dir(output_dir)
              save_im_path = get_save_image_name(
                  org_im, org_im_path, output_dir
              )
              cv2.imwrite(save_im_path, sr)
              print("save image at: ", save_im_path)
              result["save_path"] = save_im_path
              result["data"] = sr
          else:
              result["data"] = sr
  
      return result
  
file_path: PaddleHub/modules/image/Image_editing/super_resolution/falsr_c/processor.py
imports: import base64
  import os
  import time
  import cv2
  import numpy
label_desc: Use image node_id 3 for calling a global function with example usage: postprocess(data_out, org_im, org_im_shape, org_im_path, output_dir, visualization) and returns: result